An educator’s perspective of the tidyverse

Çetinkaya-Rundel, Mine; Hardin, Johanna; Baumer, Benjamin S.; McNamara, Amelia; Horton, Nicholas J.; Rundel, Colin

doi:10.5070/t514154352

Cited by 7 publications

(3 citation statements)

References 35 publications

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“…"Tidyverse-style" is often the preferred syntax for teaching new R users as it comprises a fully-featured data science ecosystem intentionally designed to ease the learning process with improved readability. 18 By creating methods to make this ecosystem more compatible with the All of Us Researcher Workbench, data science tasks such as creating a cohort and extracting data from various database tables become more accessible to a wider range of researchers, who benefit from a consistent toolkit. 19 We have published with the package a series of tutorials with commented code and explanations for extracting and wrangling the data in different ways.…”

Section: Discussionmentioning

confidence: 99%

allofus: An R package to facilitate use of the All of Us Researcher Workbench

Smith,

Cavanaugh

2024

Preprint

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Objective: We aimed to increase research and training capacity for the All of Us community through an R package designed to reduce barriers to entry to the Researcher Workbench. Materials and Methods: We developed the open-source R package allofus, available on the R package repository CRAN. The package provides functions that address common challenges we encountered while working with All of Us Research Program data. We tested the package with standard R unit tests and in real research projects. Results: We describe how the package functions allow for an efficient workflow. We demonstrate the package's utility by creating a cohort of All of Us participants with one year of electronic health record data prior to survey completion and no previous diagnosis of Type 2 diabetes. Discussion: Despite the program's easy-to-use tools like the Cohort Builder, using All of Us data for complex research questions requires a relatively high level of technical expertise. We developed an initial set of functions that solve problems we experienced with our own research and in mentoring student projects. In conjunction with the tutorials provided with the package, these tools can reduce the barrier for entry into the All of Us research community. The package will continue to grow and develop with the All of Us Research Program. Conclusion: The allofus R package can help build community research capacity by increasing access to the All of Us Research Program data, the efficiency of its use, and the rigor and reproducibility of the resulting research.

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Section: Discussionmentioning

confidence: 99%

allofus: An R package to facilitate use of the All of Us Researcher Workbench

Smith,

Cavanaugh

2024

Preprint

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“…It simplifies data manipulation with operations connected in pipelines that use standardised and natural language vocabulary. The components of the tidyverse rank as the most frequently downloaded R packages 5 and are widely taught in Data Science and Bioinformatics programs worldwide 6 .…”

Section: Mainmentioning

confidence: 99%

Thetidyomicsecosystem: Enhancing omic data analyses

Hutchison,

Keyes,

Crowell

et al. 2023

Preprint

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The exponential growth of omic data presents challenges in data manipulation, analysis, and integration. Addressing these challenges, Bioconductor offers an extensive data analysis platform and community, while R tidy programming offers a standard data organisation and manipulation that has revolutionised data science. Bioconductor and tidy R have mostly remained independent; bridging these two ecosystems would streamline omic analysis, ease learning and encourage cross-disciplinary collaborations. Here, we introduce thetidyomicsecosystem—a suite of interoperable software that brings the vast tidy software ecosystem to omic data analysis.

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“…We taught them practices such as checking for common syntax mistakes, running individual lines or small blocks of code in isolation, and commenting out code temporarily while testing other lines of code (see other tips shared with students in S2 ). Another of our pedagogical decisions was to teach R using the ‘tidyverse’ suite of packages and provide a consistent set of syntax and vocabulary for our students [ 38 ], but courses can use functions with base or formula syntax as well [ 39 ].…”

Section: Examples Of R Markdown Assignments In Math and Biology Class...mentioning

confidence: 99%